Preprint2024
Post-training sparse attention with double sparsity
Unknown
Double Sparsity reduces KV cache access in LLMs via post-training sparse attention combining token and channel sparsity.
0Jan 1, 2024Attention Mechanisms
arXiv
AI Research
AI & ML Research Papers
A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
All Papers
5 papersConferenceInternational Conference on Machine Learning2025
GuidedQuant: Large language model quantization via exploiting end loss guidance
Jinuk Kim, Marwa El Halabi, Wonpyo Park, et al.
GuidedQuant improves post-training quantization of large language models by using end-loss guidance to better preserve model accuracy.
19Jan 1, 2025Large Language ModelsQuantization
arXiv
Preprint2026
Rlvr-world: Training world models with reinforcement learning
Unknown
Proposes post-training world models via reinforcement learning to improve their generality and task performance.
0Jan 1, 2026Reinforcement Learning
Preprint2026
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD
Dongfang Li, Xiaodong Luo, Ruoyu Sun, et al.
Full-stack optimization for post-training trillion-parameter MoE models on Ascend NPU SuperPOD, achieving 34.22% MFU and domain-specialized OR models outperforming GPT-5.4-Mini.
0Jul 22, 2026Reasoning
arXiv
JournalFrontiers of Computer Science2026
A Survey of Large Language Models
Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.
A comprehensive survey of LLM techniques across pre-training, post-training, utilization, and evaluation, synthesizing state-of-the-art insights and open challenges.
4.7kMay 9, 2026Large Language ModelsFine Tuning
arXiv